A mini-review and perspective on multicyclic peptide mimics of antibodies

Exploiting the Features of Short Peptides to Recognize Specific Cell Surface Markers

Antibodies are the macromolecules of choice to ensure specific recognition of biomarkers in biological assays. However, they present a range of shortfalls including a relatively high production cost and limited tissue penetration. Peptides are relatively small molecules able to reproduce sequences of highly specific paratopes and, although they have less biospecificity than antibodies, they offer advantages like ease of synthesis, modifications of their amino acid sequences and tagging with fluorophores and other molecules required for detection. This work presents a strategy to design peptide sequences able to recognize the CD44 hyaluronic acid receptor present in the plasmalemma of a range of cells including human bone marrow stromal mesenchymal cells. The protocol of identification of the optimal amino acid sequence was based on the combination of rational design and in silico methodologies. This protocol led to the identification of two peptide sequences which were synthesized and tested on human bone marrow mesenchymal stromal cells (hBM-MSCs) for their ability to ensure specific binding to the CD44 receptor. Of the two peptides, one binds CD44 with sensitivity and selectivity, thus proving its potential to be used as a suitable alternative to this antibody in conventional immunostaining. In the context of regenerative medicine, the availability of this peptide could be harnessed to functionalize tissue engineering scaffolds to anchor stem cells as well as to be integrated into systems such as cell sorters to efficiently isolate MSCs from biological samples including various cell subpopulations. The data here reported can represent a model for developing peptide sequences able to recognize hBM-MSCs and other types of cells and for their integration in a range of biomedical applications.

AB-Gen: Antibody Library Design with Generative Pre-trained Transformer and Deep Reinforcement Learning

Antibody leads must fulfill multiple desirable properties to be clinical candidates. Primarily due to the low throughput in the experimental procedure, the need for such multi-property optimization causes the bottleneck in preclinical antibody discovery and development, because addressing one issue usually causes another. We developed a reinforcement learning (RL) method, named AB-Gen, for antibody library design using a generative pre-trained transformer (GPT) as the policy network of the RL agent. We showed that this model can learn the antibody space of heavy chain complementarity determining region 3 (CDRH3) and generate sequences with similar property distributions. Besides, when using human epidermal growth factor receptor-2 (HER2) as the target, the agent model of AB-Gen was able to generate novel CDRH3 sequences that fulfill multi-property constraints. Totally, 509 generated sequences were able to pass all property filters, and three highly conserved residues were identified. The importance of these residues was further demonstrated by molecular dynamics simulations, consolidating that the agent model was capable of grasping important information in this complex optimization task. Overall, the AB-Gen method is able to design novel antibody sequences with an improved success rate than the traditional propose-then-filter approach. It has the potential to be used in practical antibody design, thus empowering the antibody discovery and development process. The source code of AB-Gen is freely available at Zenodo (https://doi.org/10.5281/zenodo.7657016) and BioCode (https://ngdc.cncb.ac.cn/biocode/tools/BT007341).

Optimizing Epitope Conformational Ensembles Using α-Synuclein Cyclic Peptide "Glycindel" Scaffolds: A Customized Immunogen Method for Generating Oligomer-Selective Antibodies for Parkinson's Disease

Effectively presenting epitopes on immunogens, in order to raise conformationally selective antibodies through active immunization, is a central problem in treating protein misfolding diseases, particularly neurodegenerative diseases such as Alzheimer's disease or Parkinson's disease. We seek to selectively target conformations enriched in toxic, oligomeric propagating species while sparing the healthy forms of the protein that are often more abundant. To this end, we computationally modeled scaffolded epitopes in cyclic peptides by inserting/deleting a variable number of flanking glycines ("glycindels") to best mimic a misfolding-specific conformation of an epitope of α-synuclein enriched in the oligomer ensemble, as characterized by a region most readily disordered and solvent-exposed in a stressed, partially denatured protofibril. We screen and rank the cyclic peptide scaffolds of α-synuclein in silico based on their ensemble overlap properties with the fibril, oligomer-model and isolated monomer ensembles. We present experimental data of seeded aggregation that support nucleation rates consistent with computationally predicted cyclic peptide conformational similarity. We also introduce a method for screening against structured off-pathway targets in the human proteome by selecting scaffolds with minimal conformational similarity between their epitope and the same solvent-exposed primary sequence in structured human proteins. Different cyclic peptide scaffolds with variable numbers of glycines are predicted computationally to have markedly different conformational ensembles. Ensemble comparison and overlap were quantified by the Jensen-Shannon divergence and a new measure introduced here, the embedding depth, which determines the extent to which a given ensemble is subsumed by another ensemble and which may be a more useful measure in developing immunogens that confer conformational selectivity to an antibody.

Phage Display-Derived Peptide for the Specific Binding of SARS-CoV-2

Beginning from the end of 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic swept all over the world and is still afflicting the whole global population. Given that the vaccine-manufacturing ability is limited and the virus can evolve quickly, vaccination alone may not be able to end the pandemic, thus developing fast and accurate diagnoses and effective therapeutics will always be unmet needs. Phage display peptide library has been used in screening antigen-specific peptides for the invention of novel mimic receptors/ligands. Here, we report that a 12-mer phage display peptide library has been screened against the SARS-CoV-2 receptor-binding domain (RBD), and five of the screened peptides show binding ability with the RBD protein by the enzyme-linked immune sorbent assay. The surface plasmon resonance assay further demonstrates that peptide no. 1 can specifically bind to SARS-CoV-2 RBD with a binding affinity constant (K d) of 5.8 μM. Transmission electron microscopy coupled with a magnetic bead assay further confirms that the screened peptide can specifically bind the inactivated SARS-CoV-2 virus. This SARS-CoV-2-specific peptide holds great promise as a new bioreceptor/ligand for the rapid and accurate detection of SARS-CoV-2.

Downsizing antibodies: Towards complementarity-determining region (CDR)-based peptide mimetics

Monoclonal antibodies emerged as an important therapeutic drug class with remarkable specificity and binding affinity. Nonetheless, these heterotetrameric immunoglobulin proteins come with high manufacturing and therapeutic costs which can take extraordinary proportions, besides other limitations such as their limited in cellulo access imposed by their molecular size (ca. 150 kDa). These drawbacks stimulated the development of downsized functional antibody fragments (ca. 15-50 kDa), together with smaller synthetic peptides (ca. 1-3 kDa) derived from the antibodies' crucial complementarity-determining regions (CDR). Despite the general lack of success in the literal translation of CDR loops in peptide mimetics, rational structure-based and computational approaches have shown their potential for obtaining functional CDR-based peptide mimetics. In this review, we describe the efforts made in the development of antibody and nanobody paratope-derived peptide mimetics with particular focus on the used design strategies, in addition to highlighting the challenges associated with their development.

Fast and Selective Reaction of 2-Benzylacrylaldehyde with 1,2-Aminothiol for Stable N-Terminal Cysteine Modification and Peptide Cyclization

N-terminal cysteine (Cys)-specific reactions have been exploited for protein and peptide modifications. However, existing reactions for N-terminal Cys suffer from low reaction rate, unavoidable side reactions, or poor stability for reagents or products. Herein we report a fast, efficient, and selective conjugation between 2-benzylacrylaldehyde (BAA) and 1,2-aminothiol, which involves multistep reactions including aldimine condensation, Michael addition, and reduction of imine by NaBH3CN. This conjugation proceeds with a rate constant of ∼2700 M-1 s-1 under neutral condition at room temperature to produce a pair of seven-membered ring diastereoisomers, which are stable under neutral and acidic conditions. This method enables the selective modifications of the N-terminal Cys residue without interference from the internal Cys and lysine residues, providing a useful alternative to existing approaches for site-specific peptide or protein modifications and synthesis of cyclic peptides.

Bio-Inspired Strategies for Improving the Selectivity and Sensitivity of Artificial Noses: A Review

Artificial noses are broad-spectrum multisensors dedicated to the detection of volatile organic compounds (VOCs). Despite great recent progress, they still suffer from a lack of sensitivity and selectivity. We will review, in a systemic way, the biomimetic strategies for improving these performance criteria, including the design of sensing materials, their immobilization on the sensing surface, the sampling of VOCs, the choice of a transduction method, and the data processing. This reflection could help address new applications in domains where high-performance artificial noses are required such as public security and safety, environment, industry, or healthcare.

Ordered and Isomerically Stable Bicyclic Peptide Scaffolds Constrained through Cystine Bridges and Proline Turns

Bicyclic peptides are attractive scaffolds for the design of potent protein binders and new therapeutics. However, peptide bicycles constrained through disulfide bonds are rarely stable or tolerant to sequence manipulation owing to disulfide isomerization, especially for peptides lacking a regular secondary structure. Herein, we report the discovery and identification of a class of bicyclic peptide scaffolds with ordered but irregular secondary structures. These peptides have a conserved cysteine/proline framework for directing the oxidative folding into a fused bicyclic structure that consists of four irregular turns and a 3₁₀ helix (characterized by NMR spectroscopy). This work shows that bicyclic peptides can be stabilized into ordered structures by manipulating both the disulfide bonds and proline-stabilized turns. In turn, this could inspire the design and engineering of multicyclic peptides with new structures and benefit the development of novel protein binders and therapeutics.

Design and Synthesis of Cross-Link-Dense Peptides by Manipulating Regioselective Bisthioether Cross-Linking and Orthogonal Disulfide Pairing

Existing disulfide-rich peptides, both naturally occurring and de novo designed, only represent a tiny amount of the possible sequence space because natural evolution and de novo design only keep sequences that are structurally approachable by correct disulfide pairings. To bypass this limitation for designing new peptide scaffolds beyond the natural sequence space, we dedicate to developing novel disulfide-rich peptides with predefined disulfide pairing patterns irrelevant to primary sequences. However, most of these designed peptides still suffer from disulfide rearrangements to at least one to three possible isomers. Here, we report a general and reliable strategy for the design and synthesis of a range of structurally diverse cross-link-dense peptide (CDP) scaffolds with two orthogonal disulfide bonds and a bisthioether bridge that are not subject to disulfide isomerizations. Altering the pattern of cysteine and penicillamine generates hundreds of different CDP scaffolds tolerant to extensive sequence manipulations. This work thus provides many useful scaffolds for the design of functional molecules such as protein binders with improved proteolytic stability (e.g., designed by epitope grafting).